Use AI to weather the next storm of data depreciation


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This article was written by Tara DeZao, Product Marketing Director, AdTech and MarTech at Pega

The announcement last summer that Google’s depreciation of third-party cookies has been pushed back to 2023 sparked cheers, yawns and everything in between. But the question remains: what will advertisers and marketers do with the extra time? Will they waste it and resist evolution to the end? Or will they use it to make real change in search of better business results and an improved customer experience?

There’s a scene in “My So-Called Life,” the ’90s television drama that followed a group of distraught teenagers as they navigate the traps of a suburban high school. The protagonist, Angela Chase, is curled up in the girls’ bathroom, studying frantically for an exam and demoralizing herself for not having done so sooner. Suddenly another student walks through the door and shouts triumphantly, “The copier has eaten our geometry test!” Considering the period of time and its lack of digitization, it meant the crowd of girls crammed into the bathroom had a day’s reprieve and all of them clapped triumphantly, grateful for the extra study time.

We have now arrived at our “copier ate our geometry test”. This tipping point has been a long time coming, whether or not Google has removed cookies in Chrome. Without data obsolescence, consumers continue to decline third-party cookie tracking and data storage amid persistent privacy concerns, as they have done in recent years. Various sets of government regulations around the world address these concerns. Browser and operating system restrictions, as well as tougher rules for data portability within walled gardens, have signaled major disruptions in the digital marketing environment for several years. That’s why closing the door on legacy data practices is a golden opportunity to deliver better customer experiences, a goal that continues to elude many of us in the existing landscape.

Overall, consumers are dissatisfied with the state of the Union between themselves and the digital marketing industry. We struggle with frequency, relevance, context and personalization in our engagement with them. Too often we step in with irrelevant content at the wrong time and deliver either not enough or too much personalization to consumers. Not only that, but we are wrong, and we have been for some time. And the number of consumers who have installed ad blocks since 2019 proves it: Statista reported in March that there were more than 763.5 million ad block users worldwide. We discourage consumers from even wanting to have conversations with us.

But it’s not that they don’t want to hear from us, it’s the way we talk to them that doesn’t work. When there is a real exchange of value, consumers welcome engagement. According to Merkle’s Consumer Experience Sentient Report released in April, which examines how consumers feel about brands using their data in digital marketing and advertising, about half of adult US internet users say that when brands use their data in advertising, it helps them discover (50%) and find (49%) products and services that interest them, but 44% said it often seemed invasive.

Without a doubt, there will be brands and other organizations in the digital ecosystem that resist change and retain legacy practices until the bitter end of data depreciation. But if you want to be in the camp for the best results and experiences, even if you haven’t started your transformation, now is the time and here’s how to get started.

Commit to better confidentiality and transparency on all your channels

It might sound obvious, but many organizations are not at the forefront of consumer trust, privacy, and transparency in digital marketing and advertising. And although it’s in the fine print, respecting consumer privacy always helps achieve a better result. Always be transparent about how you use customer data. Be responsive when consumers ask for information and provide clear and understandable explanations of the types of data you collect and how you use it.

Audit your data strategy and your MarTech stack

Many of today’s MarTech stacks look like a jumble of point solutions for deploying segment-based fixed marketing campaigns and as such leverage multiple types of data. Spend time auditing exposure – you might have external partners in your media ecosystem and not even know what types of data segments are being used. What is your data usage, audience targeting, and search capabilities like? What steps can you take in the future of data depreciation to roll out new types of targeting, modeling, and beyond that don’t rely on third-party data and technology? Are there new partnerships you can create to access the data you need to complete your strategy? Do some of your technologies need to be replaced?

Various alternatives to cookies are emerging to fill the data gap that is emerging for many organizations. But these solutions will not be an identical replacement. As the alternatives remain largely unproven, it becomes even more essential to identify where your business needs to strengthen or replace existing capabilities. For example, in 2020, Forrester Research defined a new type of data, zero-part data, as “data that a customer intentionally and proactively shares with a brand, which can include preference center data, purchase intentions, personal background and how the individual wishes brand to recognize it. It is basically a subset of first party data that gives its users broader contextual signals about a consumer with their consent. But this approach assumes consumers will want to participate and at the scale advertisers need to make the investment worth it. Data cohorts in which organizations share first-party data to create interest-based segment types in a confidential manner are also positioned as a viable alternative in the face of data depreciation. Google’s FloC is one example. The effectiveness of this approach remains to be determined.

Invest in AI and centralize all your data

Today’s consumer moves the web at an accelerated pace, constantly changing their context. If we, as marketers, don’t move with them, we’re missing the opportunity to connect. Fixed campaigns and rule-based customer journeys aren’t about what the customer needs or wants right now, they’re about the products and services we want to talk to them about. The only way to keep up with both the consumer and the industry as it evolves is to implement solutions that rely on AI and machine learning.

Artificial intelligence-based marketing and advertising solutions can ingest your customers’ signals as they move around the web and interact with your brand to deliver highly relevant and perfectly synchronized customer interactions. Most take advantage of predictive or adaptive modeling capabilities to predict consumer behavior, even in the face of a data depreciation storm. The most precise tools exploit both. Predictive modeling and analytics are not new to marketing and advertising technologies. Predictive analytics ingests data from historical customer interactions to try to predict customer behavior, and is mostly created by data scientists. Conversely, adaptive modeling begins without data entry and learns in real time from data collected during a customer interaction. Models are automatically created and optimized on the fly. The key to hyper-personalized and perfectly timed customer engagements is the ability to ingest immediate input and provide interaction at that moment.

These capabilities greatly reduce, and in some cases eliminate, the need for external data sources. Mainly because AI allows companies to aggregate and centralize data from across the organization for use in marketing initiatives. We keep hearing that there are brands in various industries that don’t have access to enough first-party data to survive in a post-cookie digital landscape, but many organizations are sitting on a treasure trove. . However, because it may be outside of marketing in areas of the business such as finance, customer service, operations, etc., and because they don’t have solutions that can tie it together , it is wasted.

Making these changes can seem daunting because they are. Big strategic and organizational changes are a heavy burden, but the delay has given us time to make them. And because we’re not pressed for time, we can do it right and step away from the DIY batteries of the past. We’re in the midst of a digital revolution and we’re running out of time to make the big changes brands need to make to weather the next storm of data depreciation. And isn’t it always better to fix the roof when it’s dry outside?

Tara DeZao, Product Marketing Director, AdTech and MarTech at Pega.

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